Visium
Mouse skin of body
GSM6443212
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM6443212_V19N18-026-C1_hires_image': DataArray[cyx] (3, 1818, 2000)
├── Shapes
│ └── 'GSM6443212_V19N18-026-C1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 32285)
with coordinate systems:
▸ 'GSM6443212_V19N18-026-C1', with elements:
GSM6443212_V19N18-026-C1_hires_image (Images), GSM6443212_V19N18-026-C1 (Shapes)
▸ 'GSM6443212_V19N18-026-C1_downscaled_hires', with elements:
GSM6443212_V19N18-026-C1_hires_image (Images), GSM6443212_V19N18-026-C1 (Shapes)
▸ 'GSM6443212_V19N18-026-C1_downscaled_lowres', with elements:
GSM6443212_V19N18-026-C1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("I4t1xoNKvbreUAyp0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("I4t1xoNKvbreUAyp") # stem uid: Lamin resolves it to the latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Shell
# sddb client: download the .zarr into data/
sddb-cli download I4t1xoNKvbreUAyp0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/I4t1xoNKvbreUAyp
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid I4t1xoNKvbreUAypLicense: NCBI GEO policy
Part of collection
Integrated spatial multi-omics reveals fibroblast fate during tissue repair→ 4 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- skin of body
- Modality
- RNA
- Observations (spots)
- 4,992
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,818 px
- mpp
- 4.046 µm/px
- Size
- 31.7 MB
- Sample ID
- GSM6443212
- License
- NCBI GEO policy
- Published
- Jun 24, 2021
Cite this dataset
doi.org/10.1073/pnas.2110025118 ↗ BibTeX
@article{Foster_2021,
title = {Integrated spatial multiomics reveals fibroblast fate during tissue repair},
volume = {118},
ISSN = {1091-6490},
url = {http://dx.doi.org/10.1073/pnas.2110025118},
DOI = {10.1073/pnas.2110025118},
number = {41},
journal = {Proceedings of the National Academy of Sciences},
publisher = {National Academy of Sciences},
author = {Foster, Deshka S. and Januszyk, Michael and Yost, Kathryn E. and Chinta, Malini S. and Gulati, Gunsagar S. and Nguyen, Alan T. and Burcham, Austin R. and Salhotra, Ankit and Ransom, R. Chase and Henn, Dominic and Chen, Kellen and Mascharak, Shamik and Tolentino, Karen and Titan, Ashley L. and Jones, R. Ellen and da Silva, Oscar and Leavitt, W. Tripp and Marshall, Clement D. and des Jardins-Park, Heather E. and Hu, Michael S. and Wan, Derrick C. and Wernig, Gerlinde and Wagh, Dhananjay and Coller, John and Norton, Jeffrey A. and Gurtner, Geoffrey C. and Newman, Aaron M. and Chang, Howard Y. and Longaker, Michael T.},
year = {2021},
month = Oct
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB